<xarray.Dataset>
Dimensions: (time: 2671, y: 3840, x: 4608, vis_nir: 2, soil_layers_stag: 4)
Coordinates:
* time (time) datetime64[ns] 1979-02-01T03:00:00 ... 1979-12-31T21:00:00
* x (x) float64 -2.303e+06 -2.302e+06 ... 2.303e+06 2.304e+06
* y (y) float64 -1.92e+06 -1.919e+06 ... 1.918e+06 1.919e+06
Dimensions without coordinates: vis_nir, soil_layers_stag
Data variables: (12/21)
ACCET (time, y, x) float64 dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
ACSNOM (time, y, x) float64 dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
ALBEDO (time, y, x) float64 dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
ALBSND (time, y, vis_nir, x) float64 dask.array<chunksize=(1, 960, 1, 1152), meta=np.ndarray>
ALBSNI (time, y, vis_nir, x) float64 dask.array<chunksize=(1, 960, 1, 1152), meta=np.ndarray>
COSZ (time, y, x) float64 dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
... ...
SNOWH (time, y, x) float64 dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
SOIL_M (time, y, soil_layers_stag, x) float64 dask.array<chunksize=(1, 768, 1, 922), meta=np.ndarray>
SOIL_W (time, y, soil_layers_stag, x) float64 dask.array<chunksize=(1, 768, 1, 922), meta=np.ndarray>
TRAD (time, y, x) float64 dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
UGDRNOFF (time, y, x) float64 dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
crs object ...
Attributes:
Conventions: CF-1.6
GDAL_DataType: Generic
TITLE: OUTPUT FROM WRF-Hydro v5.2.0-beta2
code_version: v5.2.0-beta2
model_configuration: retrospective
model_initialization_time: 1979-02-01_00:00:00
model_output_type: land
model_output_valid_time: 1979-02-01_03:00:00
model_total_valid_times: 472
proj4: +proj=lcc +units=m +a=6370000.0 +b=6370000.0 ...
- time: 2671
- y: 3840
- x: 4608
- vis_nir: 2
- soil_layers_stag: 4
time
(time)
datetime64[ns]
1979-02-01T03:00:00 ... 1979-12-...
- long_name :
- valid output time
- standard_name :
- time
- valid_max :
- 4862880
- valid_min :
- 4778100
array(['1979-02-01T03:00:00.000000000', '1979-02-01T06:00:00.000000000',
'1979-02-01T09:00:00.000000000', ..., '1979-12-31T15:00:00.000000000',
'1979-12-31T18:00:00.000000000', '1979-12-31T21:00:00.000000000'],
dtype='datetime64[ns]')
x
(x)
float64
-2.303e+06 -2.302e+06 ... 2.304e+06
- _CoordinateAxisType :
- GeoX
- long_name :
- x coordinate of projection
- resolution :
- 1000.0
- standard_name :
- projection_x_coordinate
- units :
- m
array([-2303499.25, -2302499.25, -2301499.25, ..., 2301500.75, 2302500.75,
2303500.75])
y
(y)
float64
-1.92e+06 -1.919e+06 ... 1.919e+06
- _CoordinateAxisType :
- GeoY
- long_name :
- y coordinate of projection
- resolution :
- 1000.0
- standard_name :
- projection_y_coordinate
- units :
- m
array([-1919500.375, -1918500.375, -1917500.375, ..., 1917499.625,
1918499.625, 1919499.625])
ACCET
(time, y, x)
float64
dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- Accumulated total ET
- units :
- mm
- valid_range :
- [-100000, 100000000]
|
Array |
Chunk |
Bytes |
352.13 GiB |
5.40 MiB |
Shape |
(2671, 3840, 4608) |
(1, 768, 922) |
Dask graph |
66775 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
ACSNOM
(time, y, x)
float64
dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- accumulated melting water out of snow bottom
- units :
- mm
- valid_range :
- [0, 10000000]
|
Array |
Chunk |
Bytes |
352.13 GiB |
5.40 MiB |
Shape |
(2671, 3840, 4608) |
(1, 768, 922) |
Dask graph |
66775 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
ALBEDO
(time, y, x)
float64
dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- Surface albedo
- units :
- -
- valid_range :
- [0, 100]
|
Array |
Chunk |
Bytes |
352.13 GiB |
5.40 MiB |
Shape |
(2671, 3840, 4608) |
(1, 768, 922) |
Dask graph |
66775 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
ALBSND
(time, y, vis_nir, x)
float64
dask.array<chunksize=(1, 960, 1, 1152), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- snowpack albedo, direct
- units :
- -
- valid_range :
- [0, 100]
|
Array |
Chunk |
Bytes |
704.27 GiB |
8.44 MiB |
Shape |
(2671, 3840, 2, 4608) |
(1, 960, 1, 1152) |
Dask graph |
85472 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
ALBSNI
(time, y, vis_nir, x)
float64
dask.array<chunksize=(1, 960, 1, 1152), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- snowpack albedo, diffuse
- units :
- -
- valid_range :
- [0, 100]
|
Array |
Chunk |
Bytes |
704.27 GiB |
8.44 MiB |
Shape |
(2671, 3840, 2, 4608) |
(1, 960, 1, 1152) |
Dask graph |
85472 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
COSZ
(time, y, x)
float64
dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- Cosine of zenith angle
- units :
- -
- valid_range :
- [-100, 100]
|
Array |
Chunk |
Bytes |
352.13 GiB |
5.40 MiB |
Shape |
(2671, 3840, 4608) |
(1, 768, 922) |
Dask graph |
66775 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
EDIR
(time, y, x)
float64
dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- Direct from soil evaporation rate
- units :
- kg m-2 s-1
- valid_range :
- [-10000000, 10000000]
|
Array |
Chunk |
Bytes |
352.13 GiB |
5.40 MiB |
Shape |
(2671, 3840, 4608) |
(1, 768, 922) |
Dask graph |
66775 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
FIRA
(time, y, x)
float64
dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- Total net LW radiation to atmosphere
- units :
- W m-2
- valid_range :
- [-15000, 15000]
|
Array |
Chunk |
Bytes |
352.13 GiB |
5.40 MiB |
Shape |
(2671, 3840, 4608) |
(1, 768, 922) |
Dask graph |
66775 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
FSA
(time, y, x)
float64
dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- Total absorbed SW radiation
- units :
- W m-2
- valid_range :
- [-15000, 15000]
|
Array |
Chunk |
Bytes |
352.13 GiB |
5.40 MiB |
Shape |
(2671, 3840, 4608) |
(1, 768, 922) |
Dask graph |
66775 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
FSNO
(time, y, x)
float64
dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- Snow-cover fraction on the ground
- units :
- 1
- valid_range :
- [0, 1000]
|
Array |
Chunk |
Bytes |
352.13 GiB |
5.40 MiB |
Shape |
(2671, 3840, 4608) |
(1, 768, 922) |
Dask graph |
66775 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
HFX
(time, y, x)
float64
dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- Total sensible heat to the atmosphere
- units :
- W m-2
- valid_range :
- [-15000, 15000]
|
Array |
Chunk |
Bytes |
352.13 GiB |
5.40 MiB |
Shape |
(2671, 3840, 4608) |
(1, 768, 922) |
Dask graph |
66775 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
LH
(time, y, x)
float64
dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- Total latent heat to the atmosphere
- units :
- W m-2
- valid_range :
- [-15000, 15000]
|
Array |
Chunk |
Bytes |
352.13 GiB |
5.40 MiB |
Shape |
(2671, 3840, 4608) |
(1, 768, 922) |
Dask graph |
66775 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
QRAIN
(time, y, x)
float64
dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- Rainfall rate on the ground
- units :
- mm s-1
- valid_range :
- [0, 10000000]
|
Array |
Chunk |
Bytes |
352.13 GiB |
5.40 MiB |
Shape |
(2671, 3840, 4608) |
(1, 768, 922) |
Dask graph |
66775 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
QSNOW
(time, y, x)
float64
dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- Snowfall rate on the ground
- units :
- mm s-1
- valid_range :
- [0, 10000000]
|
Array |
Chunk |
Bytes |
352.13 GiB |
5.40 MiB |
Shape |
(2671, 3840, 4608) |
(1, 768, 922) |
Dask graph |
66775 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
SNEQV
(time, y, x)
float64
dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- Snow water equivalent
- units :
- kg m-2
- valid_range :
- [0, 1000000]
|
Array |
Chunk |
Bytes |
352.13 GiB |
5.40 MiB |
Shape |
(2671, 3840, 4608) |
(1, 768, 922) |
Dask graph |
66775 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
SNOWH
(time, y, x)
float64
dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- Snow depth
- units :
- m
- valid_range :
- [0, 1000000]
|
Array |
Chunk |
Bytes |
352.13 GiB |
5.40 MiB |
Shape |
(2671, 3840, 4608) |
(1, 768, 922) |
Dask graph |
66775 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
SOIL_M
(time, y, soil_layers_stag, x)
float64
dask.array<chunksize=(1, 768, 1, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- volumetric soil moisture, the dimensionless ratio of water volume (m3) to soil volume (m3)
- units :
- m3 m-3
- valid_range :
- [0, 100]
|
Array |
Chunk |
Bytes |
1.38 TiB |
5.40 MiB |
Shape |
(2671, 3840, 4, 4608) |
(1, 768, 1, 922) |
Dask graph |
267100 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
SOIL_W
(time, y, soil_layers_stag, x)
float64
dask.array<chunksize=(1, 768, 1, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- liquid volumetric soil moisture
- units :
- m3 m-3
- valid_range :
- [0, 100]
|
Array |
Chunk |
Bytes |
1.38 TiB |
5.40 MiB |
Shape |
(2671, 3840, 4, 4608) |
(1, 768, 1, 922) |
Dask graph |
267100 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
TRAD
(time, y, x)
float64
dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- Surface radiative temperature
- units :
- K
- valid_range :
- [0, 4000]
|
Array |
Chunk |
Bytes |
352.13 GiB |
5.40 MiB |
Shape |
(2671, 3840, 4608) |
(1, 768, 922) |
Dask graph |
66775 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
UGDRNOFF
(time, y, x)
float64
dask.array<chunksize=(1, 768, 922), meta=np.ndarray>
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- grid_mapping :
- crs
- long_name :
- Accumulated underground runoff
- units :
- mm
- valid_range :
- [-10000, 10000000]
|
Array |
Chunk |
Bytes |
352.13 GiB |
5.40 MiB |
Shape |
(2671, 3840, 4608) |
(1, 768, 922) |
Dask graph |
66775 chunks in 2 graph layers |
Data type |
float64 numpy.ndarray |
|
|
crs
()
object
...
- GeoTransform :
- -2303999.17655 1000.0 0 1919999.66329 0 -1000.0
- _CoordinateAxes :
- y x
- _CoordinateTransformType :
- Projection
- earth_radius :
- 6370000.0
- esri_pe_string :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- false_easting :
- 0.0
- false_northing :
- 0.0
- grid_mapping_name :
- lambert_conformal_conic
- inverse_flattening :
- 0.0
- latitude_of_projection_origin :
- 40.0
- long_name :
- CRS definition
- longitude_of_central_meridian :
- -97.0
- longitude_of_prime_meridian :
- 0.0
- semi_major_axis :
- 6370000.0
- spatial_ref :
- PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
- standard_parallel :
- [30.0, 60.0]
- transform_name :
- lambert_conformal_conic
[1 values with dtype=object]
PandasIndex
PandasIndex(DatetimeIndex(['1979-02-01 03:00:00', '1979-02-01 06:00:00',
'1979-02-01 09:00:00', '1979-02-01 12:00:00',
'1979-02-01 15:00:00', '1979-02-01 18:00:00',
'1979-02-01 21:00:00', '1979-02-02 00:00:00',
'1979-02-02 03:00:00', '1979-02-02 06:00:00',
...
'1979-12-30 18:00:00', '1979-12-30 21:00:00',
'1979-12-31 00:00:00', '1979-12-31 03:00:00',
'1979-12-31 06:00:00', '1979-12-31 09:00:00',
'1979-12-31 12:00:00', '1979-12-31 15:00:00',
'1979-12-31 18:00:00', '1979-12-31 21:00:00'],
dtype='datetime64[ns]', name='time', length=2671, freq=None))
PandasIndex
PandasIndex(Float64Index([-2303499.25, -2302499.25, -2301499.25, -2300499.25, -2299499.25,
-2298499.25, -2297499.25, -2296499.25, -2295499.25, -2294499.25,
...
2294500.75, 2295500.75, 2296500.75, 2297500.75, 2298500.75,
2299500.75, 2300500.75, 2301500.75, 2302500.75, 2303500.75],
dtype='float64', name='x', length=4608))
PandasIndex
PandasIndex(Float64Index([-1919500.375, -1918500.375, -1917500.375, -1916500.375,
-1915500.375, -1914500.375, -1913500.375, -1912500.375,
-1911500.375, -1910500.375,
...
1910499.625, 1911499.625, 1912499.625, 1913499.625,
1914499.625, 1915499.625, 1916499.625, 1917499.625,
1918499.625, 1919499.625],
dtype='float64', name='y', length=3840))
- Conventions :
- CF-1.6
- GDAL_DataType :
- Generic
- TITLE :
- OUTPUT FROM WRF-Hydro v5.2.0-beta2
- code_version :
- v5.2.0-beta2
- model_configuration :
- retrospective
- model_initialization_time :
- 1979-02-01_00:00:00
- model_output_type :
- land
- model_output_valid_time :
- 1979-02-01_03:00:00
- model_total_valid_times :
- 472
- proj4 :
- +proj=lcc +units=m +a=6370000.0 +b=6370000.0 +lat_1=30.0 +lat_2=60.0 +lat_0=40.0 +lon_0=-97.0 +x_0=0 +y_0=0 +k_0=1.0 +nadgrids=@null +wktext +no_defs